Filtry
wszystkich: 1164
-
Katalog
- Publikacje 893 wyników po odfiltrowaniu
- Czasopisma 44 wyników po odfiltrowaniu
- Konferencje 9 wyników po odfiltrowaniu
- Osoby 61 wyników po odfiltrowaniu
- Projekty 3 wyników po odfiltrowaniu
- Kursy Online 18 wyników po odfiltrowaniu
- Wydarzenia 2 wyników po odfiltrowaniu
- Dane Badawcze 134 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: color, emotion, machine learning, qualitative research, survey appraisal
-
Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
-
Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
-
Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
-
Machine Dynamics Research
Czasopisma -
Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
-
Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
Publikacja -
Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
Publikacja -
Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
Publikacja -
Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
Publikacja -
A survey of medical researchers indicates poor awareness of research data management processes and a role for data librarians
Publikacja -
SIMULATION AND EXPERIMENTAL RESEARCH OF CLAW POLE MACHINE WITH A HYBRID EXCITATION AND LAMINATED ROTOR CORE
Publikacja -
Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
Publikacja -
Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
-
Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
Publikacja -
Qualitative Research in Organizations and Management
Czasopisma -
Qualitative Research in Financial Markets
Czasopisma -
Global Qualitative Nursing Research
Czasopisma -
Qualitative Research Reports in Communication
Czasopisma -
Qualitative Research in Accounting and Management
Czasopisma -
Departures in Critical Qualitative Research
Czasopisma -
Edyta Gołąb-Andrzejak dr hab.
Osoby -
Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
Publikacja -
Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
-
Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
Publikacja -
Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
-
Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublikacjaThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
-
Julita Wasilczuk dr hab.
OsobyUrodzona 5 kwietnia 1965 roku w Gdańsku. W latach 1987–1991 odbyła studia na Wydziale Ekonomiki Transportu Uniwersytetu Gdańskiego (obecnie Wydział Ekonomii). Od 1993 roku zatrudniona na nowo utworzonym Wydziale Zarządzania i Ekonomii, Politechniki Gdańskiej, na stanowisku asystenta. W 1997 roku uzyskała stopień doktora nauk ekonomicznych na WZiE, a w 2006 doktora habilitowanego nauk ekonomicznych w dyscyplinie nauki o zarządzaniu,...
-
Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublikacjaIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
-
JOURNAL OF MACHINE LEARNING RESEARCH
Czasopisma -
International Conference on Qualitative Research in IT & IT in Qualitative Research
Konferencje -
A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
-
Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
Publikacja -
Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
Publikacja -
Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
-
Learning Environments Research
Czasopisma -
Research in Learning Technology
Czasopisma -
Frontline Learning Research
Czasopisma -
A Concept of Automatic Film Color Grading Based on Music Recognition and Evoked Emotions
PublikacjaThe article presents the aspects of the final selection of the color of shots in film production based on the psychology of color. First of all, the elements of color processing, contrast, saturation or white balance in the film shots were presented and the definition of color grading was given. In the second part of the article the analysis of film music was conducted in the context of stimulating appropriate emotions while watching...
-
Kamila Kokot-Kanikuła mgr
OsobyKamila Kokot-Kanikuła pracuje w Bibliotece Politechniki Gdańskiej w Sekcji Budowy Zbiorów Cyfrowych i Multimedialnych na stanowisku starszego bibliotekarza. Jest absolwentką Instytutu Historycznego oraz Informacji Naukowej i Bibliotekoznawstwa na Uniwersytecie Wrocławskim. Główne kierunki zainteresowań to starodruki, biblioteki cyfrowe, repozytoria instytucjonalne, Otwarte Zasoby Edukacyjne, Open Access i Open Data. W bibliotece...
-
Qualitative Research in Sport Exercise and Health
Czasopisma -
Journal of Qualitative Research in Health Science
Czasopisma -
European Journal for Qualitative Research in Psychotherapy
Czasopisma -
Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
-
Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
-
Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
Publikacja -
Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
Publikacja -
Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
Publikacja -
Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
-
Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
-
Michał Grochowski dr hab. inż.
OsobyProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...